Overview
- Describes recent advances in RGB-D based computer vision algorithms, with an emphasis on advanced machine learning techniques for interpreting the RGBD information
- Covers a range of different techniques from computer vision, machine learning, audio, speech and signal processing, communications, artificial intelligence and media technology
- Includes contributions from leading researchers in this area, with strong industrial-research experience of the practical issues
- Includes supplementary material: sn.pub/extras
Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)
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Keywords
Table of contents (14 chapters)
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Reconstruction, Mapping and Synthesis
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Detection, Segmentation and Tracking
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Learning-based Recognition
Editors and Affiliations
About the editors
Dr. Ling Shao is a Senior Lecturer (Associate Professor) in the Department of Electronic and Electrical Engineering at the University of Sheffield, UK. His publications include the Springer title Multimedia Interaction and Intelligent User Interfaces.
Dr. Jungong Han is a Senior Scientist at Civolution Technology, Eindhoven, and a Guest Researcher at the Eindhoven University of Technology, Netherlands.
Dr. Pushmeet Kohli is a Senior Researcher in the Machine Learning and Perception Group at Microsoft Research Cambridge and an Associate in the Psychometrics Centre at the University of Cambridge, UK.
Dr. Zhengyou Zhang, IEEE Fellow and ACM Fellow, is a Principal Researcher and Research Manager of the Multimedia, Interaction, and Communication Group at Microsoft Research Redmond, WA, USA.
Bibliographic Information
Book Title: Computer Vision and Machine Learning with RGB-D Sensors
Editors: Ling Shao, Jungong Han, Pushmeet Kohli, Zhengyou Zhang
Series Title: Advances in Computer Vision and Pattern Recognition
DOI: https://doi.org/10.1007/978-3-319-08651-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-08650-7Published: 05 August 2014
Softcover ISBN: 978-3-319-38105-3Published: 17 September 2016
eBook ISBN: 978-3-319-08651-4Published: 14 July 2014
Series ISSN: 2191-6586
Series E-ISSN: 2191-6594
Edition Number: 1
Number of Pages: X, 316
Number of Illustrations: 15 b/w illustrations, 148 illustrations in colour
Topics: Image Processing and Computer Vision, Artificial Intelligence, User Interfaces and Human Computer Interaction